ECON 5575

Econometrics I

Lec 01 selected

This course is designed to introduce students to commonly used econometric concepts and methods in economic research. It will examine both the classical linear regression model and linear models under more general assumptions (heteroscedasticity, autocorrelation, multicollinearity), with a focus on estimation, inference, and forecasting. It also provides an introduction to asymptotic theory and maximum likelihood approach.

Sections

Lecture

From the syllabus

From the Fall 2026 syllabus by Yulia Kotlyarova. Open the PDF

Grading

30%Assignments (4)Dates to be determined
25%MidtermNov 4, tentative; 80 minutes, in person
45%Final exam3 hours, in person; cumulative

Textbooks

  • Econometric Theory and Methods, R. Davidson and J. MacKinnon (free)
  • Econometric Analysis, W. H. Greene (optional)
  • Econometrics, B. Hansen (optional)
  • Econometric Methods with Applications in Business and Economics, C. Heij, P. de Boer, P. H. Franses, T. Kloek, and H. K. van Dijk (optional, free)
  • Probability Theory and Statistical Inference: Econometric Modeling with Observational Data, A. Spanos (optional, free)
  • Econometric Analysis of Cross Section and Panel Data, J. M. Wooldridge (optional)

Course rules

Missed midterm
There is no make-up; with a valid reason, notify the instructor by exam day and the final counts for 70%.
Late assignments
For a valid reason, contact the instructor before the deadline to discuss alternative arrangements.
Missed final
For a valid reason, notify the instructor as soon as possible; a make-up final is available.
Collaboration
Students may not collaborate on assignments or exams.
Generative AI
Use of generative AI is not permitted.

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